Method And System For Evaluating Sensor Data From A Well Service Rig

ABSTRACT

As activities are completed at a well service rig, sensors receive data and transmit it to a computer or database for storage. The sensor data, including the time it takes to complete particular activities on the rig, is evaluated to determine benchmarks. For example, data from multiple instances of an activity is organized and evaluated to determine the median value for data in that activity. Outlier data is removed and the new median and moving range is determined. A natural process limit range is then determined based on the moving range and data for each instance is compared to the natural process limit range. Instances that have data outside of the natural process limit range are noted and go through supplemental analysis to determine why the data was outside of the natural process limit range. The data can also be evaluated against activity benchmarks to determine if an activity was completed properly.

RELATED PATENT APPLICATION

This application is a divisional application of and claims priorityunder 35 U.S.C. §120 to U.S. Nonprovisional patent application Ser. No.13/283,473, filed Oct. 27, 2011, and titled “Method and System forEvaluating Sensor Data From a Well Service Rig,” which claims priorityunder 35 U.S.C. §119 to U.S. Provisional Patent Application Ser. No.61/407,427, filed Oct. 27, 2010, and titled “Methods of EvaluatingSensor Data From a Well Service Rig and Calculating Upper and LowerOperating Limits for Activity Data from a Well Service Rig,” the entirecontents of both which are hereby incorporated herein by referenceherein for all purposes.

TECHNICAL FIELD

The present disclosure relates generally to evaluation of sensor dataconcerning servicing hydrocarbon wells and more specifically to anevaluation of sensor data obtained from a computerized work over rigadapted to record and transmit sensor data concerning well servicingactivities and conditions at a well site.

BACKGROUND

After drilling a hole through a subsurface formation and determiningthat the formation can yield an economically sufficient amount of oil orgas a crew completes the well. Once completed, a variety of events mayoccur to the formation causing the well and its equipment to require a“work-over.” For purposes of this application, “work-over” and “service”operations are used in their very broadest sense to refer to allactivities performed on or for a well to repair or rehabilitate thewell, and also includes activities to shut in or cap the well.Generally, workover operations include such things as replacing worn ordamaged parts (e.g., a pump, sucker rods, tubing, and packer glands),applying secondary or tertiary recovery techniques, such as chemical orhot oil treatments, cementing the wellbore, and logging the wellbore, toname just a few.

During drilling, completion, and well servicing, personnel routinelyinsert into and/or extract equipment such as tubing, tubes, pipes, rods,hollow cylinders, casing, conduit, collars, and duct from the well. Forexample, a service crew may use a workover or service rig (collectivelyhereinafter “service rig” or “rig”) that is adapted to complete a numberof activities at the well, including, but not limited to, pulling thewell tubing or rods out of the well, setting tubing anchors, and also torun the tubing or rods back into the well. Typically, these mobileservice rigs are motor vehicle-based and have an extendible, jack-upderrick complete with draw works and block and have numerous sensorsthat receive data as the activities are being completed at the well. Inmost cases the data from these sensors and other input devices arerecorded and stored in case they need to be subsequently evaluated. Overtime, a significant amount of data for numerous instances of an activitycompleted on different rigs and by different work crews is collected.Finding ways to use that data to improve operations, evaluating whetheractivities are being completed properly and improve safety for the rigcrew would improve the overall operation of the rig as it completes theactivities in the future.

SUMMARY

The exemplary embodiments described herein describe systems and methodsfor evaluating sensor, time and activity data obtained by a well servicerig or vehicle while it is conducting activities near a well and usingthat evaluation of data to, for example, determine if the activity wascompleted properly, set benchmarks based on an evaluation of numerousactivities and compare data to the benchmarks to determine instances ofactivities that are outside a natural process limits for that particularbenchmark. For one aspect of the present invention, acomputer-implemented method for evaluating data from a well service rigcan include the step of receiving a collection of data, wherein thecollection of data includes data for multiple instances of an activitycompleted by a well service rig at a wellsite. The method can alsoinclude the step of conducting a gross error review of the collection ofdata. In addition, the method can include the step of conducting a techlimit activity review of the collection of data. Furthermore, theexemplary method can include the step of generating a report for theinstances of the activity.

For another aspect of the present invention, a computer-implementedmethod for determining a trip activity coefficient for an activitycompleted by a well service rig can include the step of receiving, amultiple data entries for a single instance of the activity completed bythe well service rig. The method can also include the step of evaluatinga first portion of the multiple data entries to determine a gross timeor total time to complete the activity. The method can also include thestep of evaluating another portion of the multiple data entries todetermine a portion of the gross time that the well service rigconducted operations during the instance of the activity and candesignate that portion of the gross time as work time. In addition, theexemplary method can include the step of calculating the trip activitycoefficient for that instance of the activity.

For yet another aspect of the present invention, a computer-implementedmethod for determining if a tubing anchor was set properly by a wellservice rig can include the step of receiving multiple entries of loaddata collected during an instance of setting the tubing anchor with thewell service rig. The method can also include the step of receivingmultiple entries of block position data collected during the instance.The method can also include the step of evaluating the multiple entriesof load data to determine if there is a first portion of the load datathat increases to a string weight. In addition, the exemplary method caninclude the step of evaluating the multiple entries of block positiondata to identify a first period where a first portion of the blockposition data shows that a block is moving upward. Also, the exemplarymethod can include the step of evaluating the load data to determine ifduring the first period, the load increases a first nominal amount.Further, the exemplary method can include the step of evaluating theblock position data to determine if a second period exists after thefirst period where a second portion of the block position data showsthat the block is moving downward. The method can also include the stepof evaluating the load data to determine if during the second period,the load decreases a second nominal amount. In addition, the method caninclude the step of evaluating the block position data to determine if athird period exists after the second period where a portion of the blockposition data shows that the block is moving upward. Further, the methodcan include the step of evaluating the load data to determine if duringthe third period, the load increases a third nominal amount. Also, themethod can include the step of evaluating the block position data todetermine if a fourth period exists after the third period where aportion of the block position data shows that the block is movingdownward. The method can also include the step of evaluating the loaddata to determine if during the fourth period, the load decreases afourth nominal amount. In addition, the method can include the step ofevaluating the block position data and the load data to determine if afifth period exists after the fourth period where a fifth portion of theblock position data and the load data are substantially stable for apredetermined amount of time. Further, the method can include the stepof generating a positive notification that the tubing anchor was setproperly based on a positive determination in the determining steps.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale, and wherein:

FIG. 1 is a side view of an exemplary mobile repair unit with itsderrick extended according to one exemplary embodiment;

FIG. 2 is a side view of the exemplary mobile repair unit with itsderrick retracted according to one exemplary embodiment;

FIG. 3 is an electrical schematic of a monitor circuit according to oneexemplary embodiment;

FIG. 4 illustrates the raising and lowering of an inner tubing stringwith an exemplary mobile repair unit according to one exemplaryembodiment;

FIG. 5 illustrates one embodiment of an activity capture methodologyoutlined in tabular form according to one exemplary embodiment;

FIG. 6 provides a frontal view of an exemplary operator interfaceaccording to one exemplary embodiment;

FIG. 7 is a schematic diagram of an exemplary data management systemaccording to one exemplary embodiment;

FIG. 8 is a flow chart presenting a method for evaluating sensor andactivity data according to one exemplary embodiment;

FIG. 9 is a flow chart presenting a method for gross error review ofsensor data and activity data in accordance with one exemplaryembodiment;

FIG. 10 is a flow chart presenting a method for tech limit activityreview of sensor data and activity data in accordance with one exemplaryembodiment;

FIG. 11 is a flow chart presenting a method for conducting additionalanalysis of sensor data and activity data in accordance with oneexemplary embodiment;

FIG. 12 is a flow chart presenting a method for conducting data miningof sensor data and activity data in accordance with one exemplaryembodiment;

FIG. 13 is a flow chart presenting a method for determining the numberof stands pulled out of or run into a whole during an activity inaccordance with one exemplary embodiment;

FIG. 14 is a flow chart presenting a method for verifying that a tubinganchor catcher was set correctly in accordance with one exemplaryembodiment;

FIG. 15 is a table presenting an example of the steps in the gross errorreview and tech limit activity review of FIG. 9 for representative datain accordance with one exemplary embodiment;

FIG. 16 is a table presenting certain exemplary calculations from thegross error review and tech limit activity review of FIG. 15 inaccordance with one exemplary embodiment;

FIG. 17 is a table presenting an exemplary calculation of median fordata in the gross error review and tech limit activity review of FIG. 15in accordance with one exemplary embodiment of the present invention;

FIG. 18 is a representative job efficiency report in accordance with oneexemplary embodiment of the present invention; and

FIGS. 19A-C are a representative job summary report in accordance withone exemplary embodiment of the present invention.

The drawings illustrate only exemplary embodiments of the invention andare therefore not to be considered limiting of its scope, as theinvention may admit to other equally effective embodiments. The elementsand features shown in the drawings are not necessarily to scale,emphasis instead being placed upon clearly illustrating the principlesof the exemplary embodiments. Additionally, certain dimensions orpositionings may be exaggerated to help visually convey such principles.In the drawings, reference numerals designate like or corresponding, butnot necessarily identical, elements.

DETAILED DESCRIPTION OF THE EXEMPLARY EMBODIMENTS

Exemplary embodiments will now be described in detail with reference tothe included figures. The exemplary embodiments are described inreference to how they might be implemented. In the interest of clarity,not all features of an actual implementation are described in thisspecification. Those of ordinary skill in the art will appreciate thatin the development of an actual embodiment, severalimplementation-specific decisions must be made to achieve the inventors'specific goals, such as compliance with system-related andbusiness-related constraints which can vary from one implementation toanother. Moreover, it will be appreciated that such a development effortmight be complex and time-consuming, but would nevertheless be a routineundertaking for those of ordinary skill in the art having benefit ofthis disclosure. Further aspects and advantages of the various figuresof the invention will become apparent from consideration of thefollowing description and review of the figures. While references aregenerally made hereinafter to rods, tubing, or casing specifically, withthe description of the figures, each reference should be read broadly toinclude rods, tubing, casing, piping, and other downhole equipmentunless specifically limited therein.

The exemplary embodiments are also directed to retrieval and evaluationof sensor data obtained during activities at a workover or well-servicerig and, in certain embodiments, calculating upper and lower limits foractivity data derived from the workover or well-service rig(collectively the “well-service rig” or “rig”). The exemplaryembodiments support computer-implemented methods and systems for theretrieval and analysis of the sensor data, time data, and activity datafrom the well-service rig in a networked or stand-along computingsystem. Furthermore the exemplary system, or portions thereof, can belocated at or adjacent to the well-service rig or at a location remotefrom the well-service rig, such as a shop, business office or businessheadquarters.

In a distributed computing environment, program modules and the sensordata obtained from the well-service rig may be physically located indifferent local and remote memory storage devices or databases.Execution of the program modules may occur locally in a stand-alonemanner or remotely in a client/server manner. Examples of suchdistributed computing environments include local area networks,enterprise wide computer networks, and the global Internet.

The detailed description that follows is represented largely in terms ofprocesses and symbolic representations of operations by conventionalcomputing components, including processing units, memory storagedevices, databases, display devices, and input devices. These processesand operations may utilize conventional computer components in astand-alone or distributed computing environment.

The processes and operations performed by the computer include themanipulation of signals by a processing unit or remote computer and themaintenance of these signals within data structures resident in one ormore of the local or remote memory storage devices. Such data structuresimpose a physical organization upon the collection of data stored withina memory storage device and represent specific, electrical or magneticelements. The symbolic representations are the means used by thoseskilled in the art of computer programming and computer construction tomost effectively convey teachings and discoveries to others skilled inthe art.

Exemplary embodiments of the present invention include a computerprogram that embodies the functions described herein and illustrated inthe flowcharts. However, it should be apparent that there could be manydifferent ways of implementing the invention in computer programming,and the invention should not be construed as limited to any one set ofthe computer program instructions. Furthermore, a skilled programmerwould be able to write such a computer program to implement a disclosedembodiment of the present invention without difficulty based, forexample, on the tables and flowcharts and associated description in theapplication text. Therefore, disclosure or a particular set of programcode instructions is not considered necessary for an adequateunderstanding of how to make and use the present invention.

Referring to FIG. 1, a retractable, self-contained mobile repair unit 20is presented to include a truck frame 22 supported on wheels 24, anengine 26, a hydraulic pump 28, an air compressor 30, a firsttransmission 32, a second transmission 34, a variable speed hoist 36, ablock 38, an extendible derrick 40, a first hydraulic cylinder 42, asecond hydraulic cylinder 44, a first transducer 46, a monitor 48, andretractable feet 50.

The engine 26 selectively couples to the wheels 24 and the hoist 36 byway of the transmissions 34 and 32, respectively. The engine 26 alsodrives the hydraulic pump 28 via the line 29 and the air compressor 30via the line 31. The compressor 30 powers a pneumatic slip (Not Shown),and the pump 28 powers a set of hydraulic tongs (Not Shown). The pump 28also powers the cylinders 42 and 44 which respectively extend and pivotthe derrick 40 to selectively place the derrick 40 in a workingposition, as shown in FIG. 1, and in a lowered position, as shown inFIG. 2. In the working position, the derrick 40 is pointed upward, butits longitudinal centerline 54 is angularly offset from vertical asindicated by the angle 56. The angular offset provides the block 38access to a wellbore 58 without interference with the derrick pivotpoint 60. With the angular offset 56, the derrick framework does notinterfere with the typically rapid installation and removal of numerousinner pipe segments (known as pipe, inner pipe string, rods, or tubing62, hereinafter interchangeably referred to in a non-limiting manner as“tubing” or “rods”).

Individual pipe segments (of string 62 in FIG. 4) and sucker rods arescrewed to themselves using hydraulic tongs. The term “hydraulic tongs”used herein and below refer to any hydraulic tool that can screwtogether two pipes or sucker rods. In operation, the pump 28 drives ahydraulic motor (Not Shown) forward and reverse by way of a valve.Conceptually, the motor drives the pinions which turn a wrench elementrelative to a clamp. The element and clamp engage flats on the matingcouplings of a sucker rod or an inner pipe string 62 of one conceivedembodiment of the invention. However, it is well within the scope of theinvention to have rotational jaws or grippers that clamp on to a roundpipe (i.e., no flats) similar in concept to a conventional pipe wrench,but with hydraulic clamping. The rotational direction of the motordetermines assembly or disassembly of the couplings.

While not explicitly shown in the figures, when installing the tubingsegments 62, the pneumatic slip is used to hold the tubing 62 while thenext segment of tubing 62 is screwed on using tongs. A compressor 30provides pressurized air through a valve to rapidly clamp and releasethe slip. A tank helps maintain a constant air pressure. Pressure switchprovides the monitor 48 (FIG. 3) with a signal that indirectly indicatesthat the rig 20 is in operation.

Referring back to FIG. 1, weight applied to the block 38 is sensed byway of a hydraulic pad 92 that supports the weight of the derrick 40.The hydraulic pad 92 is basically a piston within a cylinder(alternatively a diaphragm). Hydraulic pressure in the pad 92 increaseswith increasing weight on the block 38. In FIG. 3, the first transducer46 converts the hydraulic pressure to a 0-5 VDC signal 94 that isconveyed to the monitor 48. The monitor 48 converts signal 94 to adigital value, stores it in a memory 96, associates it with a real timestamp, and eventually communicates the data to a remote computer 100 orthe computer 605, of FIG. 6, by way of hardwire, a modem 98, T1 line,WiFi, satellite, portable data storage means, such as compact disc (CD),dongle, digital video disc (DVD), tape drive, portable hard drive, discor other device or method for transferring data known to those ofordinary skill in the art.

Returning to FIG. 3, transducers 46 and 102 are shown coupled to themonitor 48. The transducer 46 indicates the pressure on the left pad 92and the transducer 102 indicates the pressure on the right pad 92. Agenerator 118 driven by the engine 26 provides an output voltageproportional to the engine speed. This output voltage is applied acrossa dual-resistor voltage divider to provide a 0-5 VDC signal at point 120and then passes through an amplifier 122. A generator 118 representsjust one of many various tachometers that provide a feedback signalproportional to the engine speed. Another example of a tachometer wouldbe to have engine 26 drive an alternator and measure its frequency. Thetransducer 80 provides a signal proportional to the pressure ofhydraulic pump 28, and thus proportional to the torque of the tongs.

A telephone accessible circuit 124, referred to as a “POCKET LOGGER” byPace Scientific, Inc. of Charlotte, N.C., includes four input channels126, 128, 130 and 132; a memory 96 and a clock 134. The circuit 124periodically samples inputs 126, 128, 130 and 132 at a user selectablesampling rate; digitizes the readings; stores the digitized values; andstores the time of day that the inputs were sampled. It should beappreciated by those skilled in the art that with the appropriatecircuit, any number of inputs can be sampled and the data could betransmitted instantaneously upon receipt.

A supervisor at a computer 100 remote from or adjacent to the work siteat which the service rig 20 is operating accesses the data stored in thecircuit 124 by way of a PC-based modem 98 or cable modem and a cellularphone 136, satellite, WiFi or other known methods for wired or wirelessdata transfer. The phone 136 reads the data stored in the circuit 124via the lines 138 (RJ11 telephone industry standard) and transmits thedata to the modem 98 by way of antennas 140 and 142.

The amplifiers 122, 144, 146 and 148 condition their input signals toprovide corresponding inputs 126, 128, 130 and 132 having an appropriatepower and amplitude range. Sufficient power is needed for RC circuits150 which briefly (e.g., 2-10 seconds) sustain the amplitude of inputs126, 128, 130 and 132 even after the outputs from transducers 46, 102and 80 and the output of the generator 118 drop off. This ensures thecapturing of brief spikes without having to sample and store anexcessive amount of data. A DC power supply 152 provides a clean andprecise excitation voltage to the transducers 46, 102 and 80; and alsosupplies the circuit 124 with an appropriate voltage by way of a voltagedivider 154. A pressure switch 90 enables the power supply 152 by way ofthe relay 156, whose contacts 158 are closed by the coil 160 beingenergized by the battery 162. FIG. 4 presents an exemplary displayrepresenting a service rig 20 lowering an inner pipe string 62 asrepresented by arrow 174 of FIG. 4.

FIG. 5 provides an illustration of an activity capture methodology intabular form according to one exemplary embodiment of the presentinvention. Now referring to FIG. 5, an operator first chooses anactivity identifier for his/her upcoming task. If “GLOBAL” is chosen,then the operator would choose from rig up/down, pull/run tubing orrods, or laydown/pickup tubing and rods (options not shown in FIG. 6).If “ROUTINE: INTERNAL” is selected, then the operator would choose fromrigging up or rigging down an auxiliary service unit, longstroke, cutparaffin, nipple up/down a BOP, fishing, jarring, swabbing, flowback,drilling, clean out, well control activities such as killing the well orcirculating fluid, unseating pumps, set/release tubing anchor,set/release packer, and pick up/laydown drill collars and/or othertools. Finally, if “ROUTINE: EXTERNAL” is chosen, the operator wouldthen select an activity that is being performed by a third party, suchas rigging up/down third party servicing equipment, well stimulation,cementing, logging, perforating, or inspecting the well, and othercommon third party servicing tasks. After the activity is identified, itis classified. For all classifications other than “ON TASK: ROUTINE,” avariance identifier is selected, and then classified using the varianceclassification values.

FIG. 6 provides a view of an rig operator interface or supervisorinterface according to one exemplary embodiment of the presentinvention. Now referring to FIG. 6, all that is required from theoperator is that he or she input in the activity data into a computer605. The operator can interface with the computer 605 using a variety ofmeans, including typing on a keyboard 625 or using a touch-screen 610.In one embodiment, a touch-screen display 610 with pre-programmedbuttons, such as pulling rods or tubing from a wellbore 615, is providedto the operator, as shown in FIG. 6, which allows the operator to simplyselect the activity from a group of pre-programmed buttons. Forinstance, if the operator were presented with the display 610 of FIG. 6upon arriving at the well site, the operator would first press the “RIGUP” button. The operator would then be presented with the option toselect, for example, “SERVICE UNIT,” “AUXILIARY SERVICE UNIT,” or “THIRDPARTY.” The operator then would select whether the activity was on task,or if there was an exception, such as WAIT TIME or MACHINE DOWN, asdescribed above. In addition, as shown in FIG. 6, prior to pulling(removing) 615 or running (inserting) rods 62, the operator could setthe high and low limits for the block 38 by pressing the learn high orlearn low buttons after moving the block 38 into the proper position.

FIG. 7 is a schematic diagram of an exemplary data management system 700for receiving and evaluating data received from sensors and from the rig20 according to one exemplary embodiment. Referring now to FIGS. 1-7,the data management system 700 includes data that is received from thesensors 38, 46, 102, 80, 118 and any other sensors on the rig 20 or usedduring an activity with the rig 20, even if not physically connected tothe rig 20. Other data, including but not limited to, timing data foreach activity from the clock 134 or other operational or activity datafrom the rig 20 is also acquired and transmitted by the system 700. Thedata is transmitted from the rig 20 or from a device near the rig to adatabase 705 and/or the computer 100 for storage and evaluation of thedata. The data can also be transmitted to the display 610 of thecomputer 605 for evaluation by the rig operator. In one exemplaryembodiment, the data is transmitted with a modem 98. Alternatively, thedata can be wired or wirelessly communicated to the computer 605,database 705 and/or computer 100 by way of electrical cable, WiFi,satellite transmission, cellular transmission or any other means of datatransmission known to those of ordinary skill in the art. While notshown in FIG. 7, the rig 20 can also include a device, such as adatabase, dongle, compact disc drive, DVD drive or similar means forrecording and storing the data at the rig 20. In addition, while theexemplary embodiment describes the system having one analysis computer100 for receiving and analyzing the data, the system 700 canalternatively include multiple general purpose computers or multiplegeneral purpose processors within a computer, set of computers ormainframe system for receiving and analyzing the data from the sensors.

FIG. 8 is a flow chart presenting a method for evaluating sensor andactivity data according to one exemplary embodiment. Referring now toFIGS. 1-8, the exemplary method 800 begins at the START step andproceeds to step 805, where an activity is conducted at the wellsite.The activity is typically conducted with the rig 20 and sensors (such asthose described in FIG. 7) record data during the activity and the clock134 records the time to complete the activity. In one exemplaryembodiment, the well-service rig 20 can be as substantially described inU.S. Pat. Nos. 6,079,490 (the “'490 Patent”) and U.S. Pat. No. 7,006,920(the “'920 Patent”), the entire contents of which are herebyincorporated herein by reference. The activities can include anyactivity typically accomplished with a well-service rig, including, butnot limited to, rig up service unit, kill well, pull out of the holerods, pick up tubing, lay down tubing, pull out of hole tubing whilescanning, run in hole tubing while hydro testing, pick up rods, lay downrods, pull out of the hole tubing, nipple-up blow out preventer (BOP),run in the hole rods, run in the hole tubing, set tubing anchor catcher,rig down the service unit.

In step 810, the sensor data and time data (which can include one ormore types of sensor data obtained by sensors on or electrically coupledor associated with the well-service rig 20) is received at the displaywhile the activity is being conducted at the wellsite by the rig 20. Thesensor and time data is transmitted or transported (when stored on aphysically transportable storage medium using, for example, a memorystick, hard drive, portable hard drive, CD, DVD, dongle or the like) tothe analysis computer 100 or “portal” or the database 705 in step 815.The terms analysis computer 100 and portal will be used interchangeablyherein. In one exemplary embodiment, the sensor and time data aretransmitted from the rig 20 by the modem 98 to the database 705 andsubsequently provided to the analysis computer 100, which iscommunicably coupled to the database 705. Alternatively, the sensor andtime data are transmitted by wired or other wireless communication fromthe rig 20 to the database 705 or analysis computer 100.

In step 820, the analysis computer 100 receives the sensor or time datafor the particular instance of the activity and receives similar sensoror time data for additional instances of the activity from the database705. In one exemplary embodiment, the activity sensor data or time datafor multiple instances of the activity have been collected from multiplewell-service rigs conducting this activity at multiple wellsites and bymultiple crews and is stored in the database 705, or other memorystorage device known to those of ordinary skill in the art, until it isanalyzed and evaluated by the analysis computer 100. In certainexemplary embodiments, the retrieval and analysis of multiple instancesof the activity are alternatively described with regards to the methodof data mining described in greater detail in FIG. 12 below. In oneexemplary embodiment, the data received at the analysis computer 100 forthe multiple instances of a particular activity is data representing theamount of time it took to complete that instance of the activity.Alternatively, other sensor data for each instance of an activity isreceived an analyzed by the analysis computer 100. Further, in certainexemplary embodiments, the analysis is completed on multiple instancesof each particular activity or sub-activity completed by the rig crew atthe wellsite.

In step 825, a gross error review of the data for the multiple instancesof the particular activity being evaluated is completed. In oneexemplary embodiment, the gross error review is completed by theanalysis computer 100. A tech limit activity review of the data for themultiple instances of the particular activity is completed in step 830.In one exemplary embodiment, the tech limit activity review is completedby the analysis computer 100. In step 835, data mining for particulardata related to one or more activities is completed in step 835. In oneexemplary embodiment, the data mining is completed by the analysiscomputer 100, which retrieves and analyzes the data being stored in thedatabase 705. Benchmarks and metrics for quality and quantitativeimprovements based on the analysis conducted in steps 825-835 for theparticular activity based on the received data are determined in step840. In certain exemplary embodiments, the benchmarks are determined bythe analysis computer 100. The process is iterative in that the processwill repeat for each activity and sub-activity for which activity datais recorded at the well service rig 20 and the data, scorecards, andreports can be updated on a daily, weekly, monthly or more or lessfrequent basis depending on the desires of the party implementing theexemplary system and methods

In step 845, an inquiry is conducted to determine if there is anotheractivity on which to conduct an analysis of sensor or time data. Thedetermination can be made by the analysis computer 100 evaluating thetypes of activities being completed by the rig 20 or the types ofactivity for which sensor or time data is stored in the database 705 orwithin the internal storage of the computer 100. If there is anotheractivity to evaluate, the YES branch is followed to step 820, where theanalysis computer 100 receives the sensor or time data for the nextactivity. Otherwise, the NO branch is followed to the END step.

FIG. 9 is a flow chart presenting a method 825 for conducting grosserror review of sensor or time data for an activity according to oneexemplary embodiment. FIG. 15 is a table presenting an example of thesteps in FIGS. 9 and 10. Now referring to FIGS. 1-9 and 15, theexemplary method 825, begins at step 905, where the analysis computer100 selects all of the individual activities associated with a group ofjobs with data stored in the memory storage device or database 705 andthen selects the first individual activity type from the multipleactivity types to analyze. In the exemplary embodiment of FIG. 15, thefirst activity type is pulling out of hole tubing (POOH tubing). In step910, the analysis computer 100 receives the sensor data or time data formultiple instances of the selected activity. In one exemplaryembodiment, the times to complete each instance of the activity arereceived by the analysis computer 100 from the memory storage device ordatabase 705. The sensor data or time data received is sorted fromlowest value to highest value in step 915. For example, when the datareceived is the completion time for each instance of the activity ofPOOH tubing, the analysis computer 100 sorts the group of completiontimes for the POOH tubing from lowest to highest. In an alternativeembodiment, the completion times or other sensor data are sorted fromhighest to lowest, sorted in another manner, or not sorted at all.

In step 920, the median data point from the received, sorted data isdetermined. In one exemplary embodiment, the analysis computer 100calculates the median data point. FIG. 16 provides one exemplary methodfor how the analysis computer 100 calculates the median data point forthe received, sorted data. The median value for the received, sorteddata is determined in step 925. In one example, the analysis computer100 calculates the median value for the received, sorted data. FIG. 17provides one exemplary method for how the analysis computer 100calculates the median value, which in this example is for completiontimes for POOH tubing.

In step 930, a determination is made for a lower level boundary (LLB)for the received sensor or time data. In one exemplary embodiment, theanalysis computer 100 determines the lower level boundary based on apre-set, pre-programmed level. In this exemplary embodiment, thepre-programmed level for the lower level boundary is the twenty-fifthpercentile of received, ordered data points and is described as aquartile. The upper level boundary (ULB) for the received sensor or timedata is determined in step 935. In one exemplary embodiment, theanalysis computer 100 determines the upper level boundary based on apre-set, pre-programmed level. In this exemplary embodiment, thepre-programmed level for the upper level boundary is the seventy-fifthpercentile of received, ordered data points and is also described as aquartile. Thus, in the example above, only the fifty percent of datapoints closest to the median data point will be used for calculating thenatural process limits and the moving range. FIG. 16 presents exemplarycalculations for determining the lower level boundary and the upperlevel boundary based on the number of received and sorted data points inthe 2^(nd) and 3^(rd) row. While the exemplary embodiment sets the lowerlevel boundary at the twenty-fifth percentile, in alternativeembodiments, the lower level boundary can be anywhere in a range between1 and 49 percent. Further, while the exemplary embodiment sets the upperlevel boundary at the seventy-fifth percentile, in alternativeembodiments the upper level boundary can be anywhere in a range between51 and 99 percent.

Once the upper and lower level boundaries have been calculated for theparticular activity, the analysis computer 100 reviews each of the datapoints to determine if they are between the upper and lower levelboundaries. If the data is between the boundaries, the “data pointbetween boundary” branch is followed to step 830. Otherwise, the“outside of boundary” branch is followed to step 945. The data pointsthat are determined to be between the upper and lower level boundariesare sometimes referred to as the “center-cut data”.

In step 945, the inner quartile (IQ) is calculated. In one exemplaryembodiment, the analysis computer calculates the inner quartile.Further, in one exemplary embodiment, the equation for determining theinner quartile is the value of the upper level boundary minus the valueof the lower level boundary or ULB-LLB=IQ. The upper gross errorboundary is determined in step 950. In one exemplary embodiment, theupper gross error boundary is determined by the analysis computer 100.In this exemplary embodiment, the upper gross error boundary iscalculated as the product of the inner quartile and a constant (C),which is then added to the upper level boundary or ULB+(C*IQ). In oneexemplary embodiment, the constant is a value of 1.5, however, othervalues ranging from 0.1-10 are within the scope and spirit of thisdisclosure. In step 955, the lower gross error boundary is determined.In one exemplary embodiment, the lower gross error boundary isdetermined by the analysis computer 100. In this exemplary embodiment,the lower gross error boundary is calculated as the product of the innerquartile and a constant (C), which is then subtracted from the lowerlevel boundary or LLB−(C*IQ). In one exemplary embodiment, the constantis a value of 1.5, however, other values ranging from 0.1-10 are withinthe scope and spirit of this disclosure.

In step 960, the data points that were outside of the boundary in step940 are selected and evaluated against the upper and lower gross errorboundaries by the analysis computer 100. In step 965, an inquiry isconducted to determine if the value of each particular data point fallswithin the upper and lower gross error boundaries. This determination istypically made by the analysis computer 100. If the data point does notfall within the upper and lower gross error boundaries, the NO branch isfollowed to step 970, where additional analysis is conducted with regardto that particular data to determine if the data value for the instanceof the activity is correct or needs to be adjusted. For example, thedata can be sent to the rig operator or rig supervisor to evaluate andcompare the electronic data against written records or other informationto determine if the electronic data that fell outside of the boundarieswas accurate. The process then continues to step 975. Returning to step965, if the data value for the instance of the activity is within theupper and lower gross error boundaries, the YES branch is followed tostep 975.

In step 975, an inquiry is conducted to determine if there is data foranother instance of the activity. If so, the YES branch is followed tostep 960. On the other hand, if there is not data for another instanceof the activity to be evaluated, the NO branch is followed to step 905to select another activity for evaluation.

FIG. 10 is a flow chart presenting a method 830 for conducting a techlimit activity review of sensor, time, or other activity data inaccordance with one exemplary embodiment. Referring now to FIGS. 1-10and 16, the exemplary method 830 begins at step 1005, where the analysiscomputer 100 sorts the center-cut data in chronological order. Themedian data point for the center-cut data is calculated in step 1010. Inone exemplary embodiment, the calculation of the median data point iscompleted by the analysis computer 100. The median data value (M) isdetermined from the center-cut data in step 1015 and can be calculatedor determined, for example, by the analysis computer 100. FIG. 16presents an exemplary calculation of the median data point and medianvalue for the exemplary center-cut data in the fourth row.

In step 1020, the moving range of the center-cut chronologically ordereddata is determined. In one exemplary embodiment, the analysis computer100 calculates the moving range for the center-cut, chronologicallyordered data. In one exemplary embodiment, the moving range is theabsolute value of the difference in two values in, for example,chronological order. Once the moving range has been calculated for thechronologically ordered data, the median (MMR) for the moving range isdetermined in step 1025. In certain exemplary embodiments, the median(mMR) for the moving range is calculated or determined by the analysiscomputer 100. In step 1030, if necessary, the upper natural processlimit (UPL) is determined. In one exemplary embodiment, thedetermination is made by the analysis computer 100 and is calculatedbased on the equation UPL=M+(X*mMR), where X is a constant. In certainexemplary embodiments, the constant X is equal to t_(σ), which issometimes referred to in the art as 3-Sigma and in certain exemplaryembodiments is equal to 3.145. Alternatively, the constant (X) can beany number between 0.5-10.

In step 1032, if necessary, the lower natural process limit (LPL) isdetermined. For certain data being evaluated it may only be compared tothe UPL, the LPL, or it may be evaluated to determine if it is between aUPL and LPL. The analysis computer 100, for example, can be programmedto know which data from which activities need be compared to whichindividual or set of natural process limits. In the example discussedabove regarding the data being completion times for a particularactivity, for example, the analysis computer 100 calculates an uppernatural process limit for completion time for the activity beinganalyzed based on the multiple instances of time completion datainitially received by the analysis computer 100 in step 820 of FIG. 8.Row 5 of FIG. 16 presents and example calculation of the 3-Sigma value.

In step 1034, once the upper natural process limit, the lower naturalprocess limit, or the upper and lower natural process limits have beencalculated, the analysis computer 100 compares each value of the sensordata or time data to the upper and/or lower natural process limits. Forexample, using the completion time for each instance of the activityexample above, only an upper natural process limit would be calculatedand the completion times for each instance of the activity would becompared to the upper natural process limit to determine whichcompletion times were greater than the upper natural process limit.Alternatively, for other types of sensor or time data, both upper andlower natural process limits or just lower natural process limits may becalculated and the sensor or time data may be compared to both upper andlower natural process limits or just the lower natural process limits asa basis for determining which instances include data that is outside ofthe natural process limit range.

An inquiry is conducted in step 1035 to determine if the data for aparticular instance of the selected activity is within the particularnatural process limit (i.e. less than the upper natural process limit,greater than the lower natural process limit or between the upper andlower natural process limits). In one exemplary embodiment, thedetermination is made by the analysis computer 100. Using the completiontimes scenario above as an example, if the completion time for theinstance is greater than the upper natural process limit value, then itwould be outside of the range and the NO branch is followed to step1040, where the analysis computer 100 flags that instance or adds thatinstance of the activity to a list of out of range instances of theactivity. The process then continues to step 1045. Returning to step1035, if the completion time for the instance is less than or equal tothe upper natural process limit value, then the value is within therange and the YES branch is followed to step 1045.

In step 1045, an inquiry is conducted by the analysis computer 100 todetermine if there is another instance of the activity to compare to thenatural process limits. If there is another instance, the YES branch isfollowed back to step 1030 to compare the data value of the nextinstance to the particular natural process limit(s). Otherwise, the NObranch is followed to step 1050. In step 1050, additional analysis isconducted on each instance of the activity that is not within thenatural process limit range. This additional analysis can be completedby the analysis computer 100, one or more supervisors over theparticular instance of the activity that was not within the naturalprocess limit(s), or a combination of both. In certain exemplaryembodiments, the additional analysis can include the supervisor or otherperson asking or answering questions to determine why the instance ofthe activity exceeded one of the natural process limits. This caninclude completing a set of drop down menus provided by the analysiscomputer 100 that describe possible reasons why the instance of theactivity was outside of the natural process limit range. Additionally, aroot cause analysis can be conducted to determine why the data for thatparticular instance of the activity was outside of the natural processlimit range.

In step 1055, an inquiry is conducted to determine if there is anotheractivity on which to conduct analysis. In one exemplary embodiment, thedetermination is made by the analysis computer 100 reviewing the dataand the types of activity associated with the data in the database 705.If there is another activity, the YES branch is followed to step 820 ofFIG. 8 to receive the data for multiple instances of the next activity.Otherwise, the NO branch is followed to step 835 of FIG. 8. In oneexemplary embodiment, the analysis computer 100 continues to loopthrough the process until all of the activities have been analyzed.Based on the data obtained, the analysis computer 100 generates reports,such as the job efficiency report of FIG. 18 or the job summary reportof FIGS. 19A-C.

FIG. 11 is a flow chart presenting an exemplary method for conductingadditional analysis of sensor data or time data as described in step1050 of FIG. 10. Referring to FIGS. 1-11, the exemplary method 1050begins at step 1105 where the analysis computer 100 determines thesupervisor for each instance of the activity that is determined to beoutside of the natural process limit(s) range. In one exemplaryembodiment, the instance in the database 705 can include additionalinformation such as rig number, job number, job site location,supervisor or other identifying information to assist the analysiscomputer 100 in determining who the supervisor is for the particularinstance that is out of range. In step 1110, the analysis computer 100transmits a request to the supervisor to complete a root cause analysisroutine. The root cause analysis routine can be sent by the analysiscomputer 100 to the supervisor with the request or a link can beprovided, or the supervisor can access the root cause analysis routineremotely. The root cause analysis routine can be stored on the analysiscomputer 100 or another computer system capable of electronicallycommunicating with the analysis computer 100.

A series of questions are provided to the supervisor based on theparticular activity to determine the reason why the particular instanceof the activity was outside of the natural process limit(s) range instep 1115. In one exemplary embodiment, the questions are provided bythe analysis computer 100 in a set of drop down menus that describepossible reasons why the instance of the activity was outside of thenatural process limit(s) range. Responses are accepted from thesupervisor in step 1120 at, for example, the analysis computer 100 oranother computer communicably coupled to the analysis computer 100. Theresponses are stored for later evaluation in step 1125. In one exemplaryembodiment, the responses are stored in the database 705 by the analysiscomputer 100. The process then continues to step 1055 of FIG. 10.

FIG. 12 is a flow chart presenting an exemplary method for conductingdata mining of sensor data or time data for activities as described instep 835 of FIG. 8. Referring now to FIGS. 1-8 and 12, the exemplarymethod 835 begins at step 1205 where the analysis computer 100 selectsor receives data for a single instance of an activity from the database705. For the ease of discussion, the following example will be describedin reference to retrieving and evaluating instances of the time tocomplete a particular activity. However, the data mining process couldalso be used on other sensor and time data for the well service rig 20.In one exemplary embodiment, the data is obtained from the database 705.In step 1210, the elapsed time for the selected instance of the activityis reviewed. In one exemplary embodiment, this review is completed bythe analysis computer 100. The analysis computer 100 designates thetotal time shown or elapsed for the selected instance as “Gross Time” instep 1215.

In step 1220, the analysis computer 100 evaluates other sensor dataassociated with this instance of the activity. In one exemplaryembodiment, the other sensor data includes inputs or selections made bythe operator at the display 610 of the computer 605, which can also bestored in the database 705. An inquiry is conducted in step 1225 todetermine if the operator indicated any wait time while completing thisinstance of the activity. In one exemplary embodiment the indication ofwait time can be made by an operator selecting one of the buttons on thedisplay 610 of the computer 605. Alternatively, the analysis computer100 can evaluate other sensor data, such as engine revolutions perminute (RPMs), hookload or rig weight from sensors 46, 102 and hydraulicpressure from sensor 80 to determine if the rig 20 was waiting during aparticular activity. If wait time was indicated, the YES branch isfollowed to step 1230, wherein the analysis computer 100 subtracts theamount of wait time from the Gross Time to determine the “Net Time” tocomplete the particular instance of the activity. The process thencontinues to step 1235. Returning to step 1225, if no wait time isindicated or determined, the NO branch is followed to step 1235, wherethe analysis computer 100 analyzes sensor data to determine what portionof the Net Time the rig was operating on the designated activity. In oneexemplary embodiment, the analysis computer 100 or the computer 605evaluates block movement over time and gaps or lack of block movementover time. When the computer 100 or 605 determines that the block is notmoving, it can designate that time that the rig 20 was not completingthe activity. In certain exemplary embodiments, the computer 100 or 605,allows for a certain amount of no activity time from the block databefore beginning to count that time as time that the rig is notcompleting the activity. For example, in one exemplary embodiment, thecomputer 100 or 605 waits until the block has not shown activity for twominutes, before beginning to count the time as time the rig 20 was notcompleting activity. In alternative embodiments, the baseline noactivity time can be an amount other than two minutes, such as anyamount of time between zero and twenty minutes. Once it determines thatthe block has not moved for longer than the designated amount of time,the computer 100 or 605 begins counting the subsequent no activity timeand when the activity is completed, subtracts that time from the NetTime. In an alternative embodiment, instead of counting only thesubsequent time, it can go back to the first moment that no activity wasdetected from the block and count that as the beginning of the noactivity time which is then subtracted from the Net Time.

In step 1240, the analysis computer 100 designates the time determinedthat the rig 20 spent operating on the particular instance of theactivity as Work Time. The trip activity coefficient is calculated instep 1245. In one exemplary embodiment, the trip activity coefficient iscalculated based on the equation of Work Time divided by Net Time and iscalculated by the analysis computer 100. In step 1250, the values forGross Time, Wait Time, Net Time, Work Time and trip activity coefficientfor this instance of the activity are digitally stored for later use. Inone exemplary embodiment, these values are stored in the database 705 bythe analysis computer 100. The analysis computer 100 determines thenumber of tubing, rods, or casing (referred to collectively hereinafterand in the claims as “tubing”) run into the hole or pulled out of thehole for this instance of the activity in step 1255.

In step 1260, an inquiry is conducted by, for example, the analysiscomputer 100 to determine if there is another instance of the activityin the database 705. If there is another instance, the YES branch isfollowed back to step 1205. Otherwise, the NO branch is followed to step840 of FIG. 8. Alternatively, the NO branch could be followed to anotherinquiry to determine with the analysis computer 100 if there is anotheractivity in the database 705 for which data mining can be completed. Inthat alternative, the YES branch would also be followed to step 1205 andthe NO branch would be followed to step 840 of FIG. 8.

FIG. 13 is a flow chart presenting an exemplary method for determining anumber of tubing joints pulled during an instance of a particularactivity, as described in step 1255 of FIG. 12. Referring now to FIGS.1-8, 12, and 13, the exemplary method 1255 begins at step 1305, wherethe analysis computer 1305 receives an activity signal. In one exemplaryembodiment, the activity signal is received based on the rig operatorselecting an activity at the display 610 which is then communicated andincluded with the data sent to the analysis computer 100. In step 1310,the start time of the tripping activity is received. For example, thestart time can be received at the analysis computer 100 either from thedatabase 705 or in real-time or nearly real time from the rig 20 by wayof the modem 98. Alternatively, the determination of the number oftubing pulled out of or run into the well is determined at the computer605. Similarly, the end time of the tripping activity is received instep 1315. The hook load, tong pressure, and block position sensor datais received in step 1320. In certain exemplary embodiments, the sensordata is received at the analysis computer 100. In step 1325, thetripping activity is classified. In one exemplary embodiment, theclassification of the tripping activity is made by the rig operator bypressing or selecting one of the buttons on the display 610. Thisclassification information is then transmitted to the database 705 orthe analysis computer 100. The analysis computer 100 sets the tubingjoint length based on the classification in step 1330.

In step 1335, the minimum block position for a single trip of running atubing string into or out of the well is received and in step 1340 themaximum block position for the same trip is received. In one exemplaryembodiment, the block position data is originates from the blockposition sensor 38 and the analysis computer 100 is able to analyzes theblock position data to determine the minimum and maximum positionsdetected for each trip into or out of the well. The maximum hookload isdetermined and received at the analysis computer 100 in step 1345 andthe minimum hookload for that same trip is determined and received atthe analysis computer 100 in step 1350. In one exemplary embodiment, themaximum and minimum hookload are based on an evaluation of the sensorreadings from the hydraulic pads 92 and the zero weight setting on thedisplay 610 that are transmitted and stored in the database 705 ordirectly transmitted to the analysis computer 100. Alternatively, thehookload levels can be provided by other weight sensing means, such asfor example, sensors or strain gauges on the block or line itself. Themaximum tong pressure during the same trip is determined and received atthe analysis computer 100 in step 1355. In one exemplary embodiment, thetong pressure data is received from the sensor 80 and the analysiscomputer 100 is able to review the series of tong pressure data todetermine the maximum pressure sensed during the single trip.

In step 1360, an inquiry is conducted to determine the differencebetween the maximum hook load received for the trip and the minimumhookload received for the trip. In one exemplary embodiment, thedifference is determined by the analysis computer 100 and the differencemust be greater than or greater than or equal to a predetermined levelor the trip will not be used for the purposes of counting the number oftubing joints. For example, the predetermined level can be five hundredpounds or any other amount between one hundred and ten thousand pounds.The determination of at least a minimum level of change in hookloadduring a trip is used by the analysis computer 100 to verify that one ormore tubing joints was either added or removed from the tubing stringduring the particular trip. If the difference in the maximum and minimumhookload is less than the predetermined level, the NO branch is followedto step 1335. If the difference in the maximum and minimum hookload isgreater than or greater than or equal to the predetermined level, thenthe YES branch is followed to step 1365. The analysis computer 100determines the difference and compares the difference to thepredetermined level, which can be preset into the computer 100 in oneexemplary embodiment.

An inquiry is conducted in step 1365 to determine if the maximum tongpressure was greater than or greater than or equal to a predeterminedtong pressure level. For example, the predetermined tong pressure levelcan be four hundred pounds per square inch (psi) or any other pressurelevel between one hundred and nine hundred psi. The determination of atleast a predetermined level of tong pressure during the trip is used bythe analysis computer 100 to verify that that tongs were engaged to makeup or break out a portion of the tubing string thereby adding orremoving from the tubing string at least one tubing joint during thetrip. If the maximum tong pressure is less than the predetermined tongpressure level, then the NO branch is followed to step 1335. However, ifthe maximum tong pressure is greater than or greater than or equal tothe predetermined tong pressure level, then the YES branch is followedto step 1370. The analysis computer 100 compares the maximum tongpressure during the trip to the predetermined tong pressure level, whichcan be preset into the computer 100 in one exemplary embodiment.

In step 1370, the analysis computer 100 estimates the number of tubingjoints based on the difference between the maximum and minimum blockpositions for the trip and the joint length. For example, the analysiscomputer can divide the difference between the maximum and minimum blockposition by the joint length and take the lowest or nearest integervalue as an estimate of the number of tubing joints. In step 1375, aninquiry is conducted to determine if there is another tripping cycle inthe data for the particular instance of the tripping activity. If so,the YES branch is followed to step 1335. Otherwise, the NO branch isfollowed to step 1380, where the analysis computer 100 sums up the totalnumber of estimated tubing joints pulled out of or run into the well forall of the trips during the particular instance of the activity. In step1380, the analysis computer 100 stores the number of tubing joints orstands with the other data for this instance of the activity. In oneexemplary embodiment, the data is stored in the database 705 orinternally on the computer 100. The process then continues to step 1260of FIG. 12.

FIG. 14 is a flow chart presenting a method for verifying that a tubinganchor catcher was set correctly according to one exemplary embodiment.Referring now to FIGS. 1-14, the exemplary method 1400 begins at step1405, where the analysis computer 100 reviews mined data in the database705. Based on the evaluation of the mined data, the analysis computer100 finds instances of activities where the activity includes settingthe tubing anchor catcher (TAC) in step 1410 and retrieves and/orevaluates the data for those instances. In certain exemplaryembodiments, the rig operator selects the set TAC activity at thedisplay 610 and this information about the activity is stored in thedatabase 705. In step 1415, the rig weight or hookload data isevaluated. In one exemplary embodiment, this data is evaluated by theanalysis computer 100.

An inquiry is conducted in step 1420 to determine if there is a sectionof the rig weight or hookload data where the hookload increases to thestring weight and holds at that string weight for a short period oftime. In one exemplary embodiment, the analysis and determination aremade by the analysis computer 100, the string weight is typically theamount of weight for the particular activity (such as the amount ofweight that is determined when the tubing string is initially picked up(minus the weight of the rig if rig weight sensors are being evaluated))and the short period of time is anywhere in the range of one second tofive minutes. If there is no such section of data, the NO branch isfollowed to step 1415. Otherwise, the YES branch is followed to step1425, where the analysis computer 100 reviews data in the database 705from the block position sensor 38 to determine a first period when theblock is moving up. In the area, that the block position data is movingup, the analysis computer reviews data from the rig weigh or hookloadsensors 46, 102 to determine if within that first period the hookload orrig weight increases a nominal amount in step 1430. In one exemplaryembodiment, a nominal increase is about 5,000 pounds. In alternativeembodiments, the nominal increase can be anywhere in the range of1500-50,000 pounds and will typically be based on the manufacturer'sspecified guidelines for the particular tubing anchor.

In step 1435, the analysis computer 100 reviews block position data todetermine if a second period exists, after the first period, where blockmovement is down and evaluates the hookload or rig weight data duringthat second period to determine if the hookload or rig weight decreasesa second nominal amount. In one exemplary embodiment, a second nominaldecrease is about 10,000 pounds. In alternative embodiments, the secondnominal decrease can be anywhere in the range of 1500-50,000 pounds andwill typically be based on the manufacturer's specified guidelines forthe particular tubing anchor. In step 1440, the analysis computer 100reviews block position data to determine if a third period exists, afterthe second period, where block movement is up and evaluates the hookloador rig weight data during that third period to determine if the hookloador rig weight increases a third nominal amount. In one exemplaryembodiment, a third nominal increase is about 15,000 pounds (or 10,000pounds over string weight). In alternative embodiments, the thirdnominal increase can be anywhere in the range of 1500-80,000 pounds andwill typically be based on the manufacturer's specified guidelines forthe particular tubing anchor.

In step 1445, the analysis computer 100 reviews block position data todetermine if a fourth period exists, after the third period, where blockmovement is down and evaluates the hookload or rig weight data duringthat fourth period to determine if the hookload or rig weight decreasesa fourth nominal amount. In one exemplary embodiment, a fourth nominaldecrease is about 20,000 pounds (or 10,000 pounds below string weight).In alternative embodiments, the fourth nominal decrease can be anywherein the range of 1500-80,000 pounds and will typically be based on themanufacturer's specified guidelines for the particular tubing anchor. Instep 1450, the analysis computer 100 reviews block position data todetermine if a fifth period exists, after the fourth period, where blockmovement is up and evaluates the hookload or rig weight data during thatfifth period to determine if the hookload or rig weight increases afifth nominal amount. In one exemplary embodiment, a fifth nominalincrease is about 20,000 pounds (or 10,000 pounds above string weight).In alternative embodiments, the fifth nominal increase can be anywherein the range of 1500-80,000 pounds and will typically be based on themanufacturer's specified guidelines for the particular tubing anchor.

In step 1455, the analysis computer 100 reviews block position data todetermine if a sixth period exists, after the fifth period, where blockmovement and the hookload or rig weight data during that fifth periodare substantially stable for a predetermined period of time. In oneexemplary embodiment, the predetermined period of time is three minutesor longer. In alternative embodiments, the predetermined period of timecan be anywhere in the range of ten seconds to twenty minutes and willtypically be based on the manufacturer's specified guidelines for theparticular tubing anchor. In step 1460, if all of the determinations insteps 1415-1455 have been verified by the analysis computer, thecomputer 100 generates a positive notification that the TAC was setproperly. In one exemplary embodiment, the notification can take theform of a designation on a report card by way of individual designationof the instance of the TAC activity and a notification of passing orsuccess on the report card or alternatively as an increase in the countof set TAC instances that were completed properly. Similarly, if one ormore of the determinations in steps 1415-1455 were not verified, theanalysis computer generates a negative notification that the TAC was notset properly in a manner similar to those described above when the TACis set properly.

In step 1460, an inquiry is conducted by the analysis computer 100 todetermine if there is another instance where the set TAC activity wasbeing completed in the database 705. If so, the YES branch is followedto step 1415. Otherwise, the NO branch is followed to step 840 of FIG.8.

Although the invention is described with reference to preferredembodiments, it should be appreciated by those skilled in the art thatvarious modifications are well within the scope of the invention.Therefore, the scope of the invention is to be determined by referenceto the claims that follow. From the foregoing, it will be appreciatedthat an embodiment of the present invention overcomes the limitations ofthe prior art. Those skilled in the art will appreciate that the presentinvention is not limited to any specifically discussed application andthat the embodiments described herein are illustrative and notrestrictive. From the description of the exemplary embodiments,equivalents of the elements shown therein will suggest themselves tothose or ordinary skill in the art, and ways of constructing otherembodiments of the present invention will suggest themselves topractitioners of the art. Therefore, the scope of the present inventionis to be limited only by any claims that follow.

We claim:
 1. A computer-implemented method for evaluating data from awell service rig comprising the steps of: receiving, at an at least oneanalysis computer, a collection of data, wherein the collection of dataincludes data for a plurality of instances of an activity completed by awell service rig at a wellsite; conducting, with the at least oneanalysis computer, a gross error review of the collection of data;conducting, with the at least one analysis computer, a tech limitactivity review of the collection of data; and generating, with the atleast one analysis computer, a report for the instances of the activity.2. The method of claim 1, further comprising the steps of: providing thewell service rig at the wellsite; conducting an instance of an activitywith the well service rig; receiving a plurality of data from aplurality of sensors at the wellsite while conducting the instance ofthe activity; transmitting the plurality of data to an area remote fromthe wellsite; and storing the plurality of data for the instance of theactivity in the data storage device.
 3. The method of claim 1, whereinthe gross error review comprises the steps of: sorting, with the atleast one analysis computer, the collection of data from a lowest valueto a highest value; determining, with the at least one analysiscomputer, a first median data point for the collection of data;determining, with the at least one analysis computer, a first mediandata value for the collection of data; applying, with the at least oneanalysis computer, a lower level boundary to the sorted collection ofdata based on a first pre-programmed percentage; applying, with the atleast one analysis computer, an upper level boundary to the sortedcollection of data based on a second pre-programmed percentage; andselecting, with the at least one analysis computer, all data points inthe sorted collection of data between the lower level boundary and theupper level boundary.
 4. The method of claim 1, wherein the firstpre-programmed percentage is within a first range between 15 percent and35 percent and wherein the second pre-programmed percentage is within asecond range between 15 percent and 35 percent.
 5. The method of claim3, wherein the tech limit activity review of the collection of datafurther comprises the steps of: sorting, with the at least one analysiscomputer, the selected data in a chronological order; determining, withthe at least one analysis computer, a second median data point for theselected, chronologically ordered data; determining, with the at leastone analysis computer, a second median value for the selected,chronologically ordered data; calculating, with the at least oneanalysis computer, a moving range for the selected, chronologicallyordered data; calculating, with the at least one analysis computer, amedian of the moving range; and calculating an upper natural processlimit, with the at least one analysis computer, based on the sum of thesecond median value and a product of a constant and the median of themoving range; and comparing, with the at least one analysis computer,data values for each instance of the collection of data against theupper natural process limit, wherein data values above the upper naturalprocess limit are out of range.
 6. The method of claim 5, furthercomprising the steps of: calculating a lower natural process limit, withthe at least one analysis computer, based on the difference of thesecond median value and the product of a constant and the median of themoving range; comparing, with the at least one analysis computer, datavalues for each instance of the collection of data against the lowernatural process limit; and designating, with the at least one analysiscomputer data values below the lower natural process limit as out ofrange.
 7. The method of claim 5, further comprising the steps of: addinginformation about each instance of the activity with data out of rangeto an out of range list; conducting additional analysis on each instanceof the activity on the out or range list;
 8. The method of claim 1,further comprising the step of determining, with the at least oneanalysis computer, a benchmark for the activity based on tech limitactivity review of the collection of data.
 9. The method of claim 1,further comprising the steps of: determining, with the at least oneanalysis computer, if there is another activity having data for aplurality of instances of the another activity in the data storagedevice; and repeating the steps of claim 1 for each additional activity.10. A computer-implemented method for determining a trip activitycoefficient for an activity completed by a well service rig comprisingthe steps of: receiving, at an at least one analysis computer, aplurality of data for a single instance of the activity completed by thewell service rig; evaluating, with the at least one analysis computer, afirst portion of the plurality of data to determine a gross time tocomplete the activity; evaluating, with the at least one analysiscomputer, a third portion of the plurality of data to determine aportion of the gross time the well service rig conducted operationsduring the instance of the activity and designating that portion of thegross time as a work time; and calculating, with the at least oneanalysis computer, the trip activity coefficient.
 11. The method ofclaim 10, further comprising the steps of: providing the well servicerig at the wellsite; conducting the instance of the activity with thewell service rig; receiving the plurality of data from a plurality ofsensors at the wellsite while conducting the instance of the activity;transmitting the plurality of data to an area remote from the wellsite;and storing the plurality of data for the instance of the activity inthe data storage device.
 12. The method of claim 10, further comprisingthe steps of: evaluating, with the at least one analysis computer, asecond portion of the plurality of data to determine an amount of waittime occurring during the instance of the activity; calculating, withthe at least one analysis computer, the difference of the gross time andthe amount of wait time as a net time; and wherein calculating the tripactivity coefficient comprises calculating the quotient of the work timedivided by the net time.
 13. The method of claim 12, further comprisingthe step of storing, with the at least one analysis computer, the grosstime, wait time, net time, work time and trip activity coefficient forthe instance of the activity in the data storage device.
 14. The methodof claim 10, wherein calculating the trip activity coefficient comprisescalculating the quotient of the work time divided by the gross time. 15.The method of claim 10, further comprising the step of calculating, withthe at least one analysis computer, a total number of tubing joints runduring the instance of the activity.
 16. The method of claim 15, whereincalculating the total number of tubing joints comprises the steps of:receiving, at the at least one analysis computer, a plurality oftripping data comprising a plurality of trips of running tubing into orout of the well; determining a joint length for each tubing joint runinto or out of the well for each trip, receiving, at the at least oneanalysis computer, a first data value representing a minimum blockposition sensed during the trip; for each trip, receiving, at the atleast one analysis computer, a second data value representing a maximumblock position sensed during the trip; for each trip, calculating, atthe at least one analysis computer, a difference between the second datavalue and the first data value as a block movement value; for each trip,calculating to a nearest integer, at the at least one analysis computer,a quotient of the block movement value divided by the joint length as atubing joint count for the trip; and calculating as a total tubing jointvalue, at the at least one analysis computer, a sum of the tubing jointcount for the plurality of trips.
 17. The method of claim 16, furthercomprising the steps of: for each trip, receiving, at the at least oneanalysis computer, a third data value representing a maximum load sensedduring the trip; for each trip, receiving, at the at least one analysiscomputer, a fourth data value representing a minimum load sensed duringthe trip; for each trip, receiving, at the at least one analysiscomputer, a fifth data value representing a maximum pressure for a tongsduring the trip; for each trip, comparing, at the at least one analysiscomputer, a difference between the third data value and the fourth datavalue is greater than a load threshold value; for each trip,determining, at the at least one analysis computer, if the fifth datavalue is greater than a pressure threshold value; and for each trip,determining, with the at least one analysis computer, that zero tubingjoints were run into or pulled out of the well if the difference betweenthe third data value and the fourth data value is not greater than theload threshold value and if the fifth data value is not greater than thepressure threshold value.
 18. The method of claim 17, wherein the loadthreshold value is between one hundred pounds and ten thousand pounds.19. The method of claim 17, wherein the pressure threshold value isbetween one hundred and nine hundred pounds per square inch.
 20. Acomputer-implemented method for determining if a tubing anchor was setproperly by a well service rig comprising the steps of: a. receiving, atan at least one analysis computer, a plurality of load data collectedduring an instance of setting the tubing anchor with the well servicerig; b. receiving, an the at least one analysis computer, a plurality ofblock position data collected during the instance; c. evaluating, withthe at least one analysis computer, the plurality of load data todetermine if there is a first portion of the plurality of load data thatincreases to a string weight; d. evaluating, with the at least oneanalysis computer, the plurality of block position data to identify afirst period where a first portion of the plurality of block positiondata identifies that a block is moving upward; e. evaluating, with theat least one analysis computer, the plurality of load data to determineif during the first period, a load represented by the load dataincreases a first nominal amount; f. evaluating, with the at least oneanalysis computer, the plurality of block position data to determine ifa second period exists after the first period where a second portion ofthe plurality of block position data identifies that the block is movingdownward; g. evaluating, with the at least one analysis computer, theplurality of load data to determine if during the second period, theload represented by the load data decreases a second nominal amount; h.evaluating, with the at least one analysis computer, the plurality ofblock position data to determine if a third period exists after thesecond period where a third portion of the plurality of block positiondata identifies that the block is moving upward; i. evaluating, with theat least one analysis computer, the plurality of load data to determineif during the third period, the load represented by the load dataincreases a third nominal amount; j. evaluating, with the at least oneanalysis computer, the plurality of block position data to determine ifa fourth period exists after the third period where a fourth portion ofthe plurality of block position data identifies that the block is movingdownward; k. evaluating, with the at least one analysis computer, theplurality of load data to determine if during the fourth period, theload represented by the load data decreases a fourth nominal amount; l.evaluating, with the at least one analysis computer, the plurality ofblock position data and the plurality of load data to determine if afifth period exists after the fourth period where a fifth portion of theplurality of block position data and a fifth portion of the plurality ofload data are substantially stable for a predetermined amount of time;and m. generating a positive notification that the tubing anchor was setproperly based on a positive determination in steps c-1.
 21. The methodof claim 20, wherein the predetermined amount of time is at least threeminutes.
 22. The method of claim 20, wherein the first nominal amount,second nominal amount, third nominal amount, and fourth nominal amountare each between 1500 pounds and 80,000 pounds.